A : Data Handling Using Pandas
1. Write a program to create a Series from ndarray
2. Write a program to find the size (length) of the Series
3. Write a program to demonstrate the use of head
4. Write a program to sort the columns
5. Write a program to find Median Additional Practicals for Practice
6. Create a panda’s series from a dictionary of values and a ndarray
7. Given a Series, print all the elements that are above the 75th percentile
8. Create a Data Frame quarterly sales where each row contains the item category, item name and expenditure. Group the rows by the category and print the total expenditure per category
9. Create a data frame for examination result and display row labels, column lables, data types of each column and the dimensions
10. Filter out rows based on different criteria such as duplicate rows
11. Importing and exporting data between pandas and CSV file
Section-B : Data Visualization Using Matplotlib
1. Given the school result data, analyses the performance of the students on different parameters, e.g. subject wise or class wise
2. For the Data frames created above, analyze and plot appropriate charts with title and legend
3. Take data of your interest from an open source (e.g. data.gov.in), aggregate and summarize it. Then plot it using different plotting functions of the Matplotlib library
Section-C : Database Query Using SQL
1. Create a student table with the student id, name and marks as attributes where the student id is the primary key
2. Insert the details of a new student in the above table
3. Delete the details of a student in the above table
4. Use the select command to get the details of the students with marks more then 80
5. Find the min, max, sum and average of the marks in a student marks table
6. Find the total number of customers from each country in the table (Customer ID, customer Name, country) using group by
7. Write a SQL query to order the (student ID, marks) table in descending order of the marks
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